The multiset representation of populations in MuGA allows the development of specific genetic operators useful for typically difficult problems. In this paper we explored an adaptation of the mutation operator and an adaptation of the replacement operator. Both use the number of copies in a multi-individual (MI) enabling MuGA to obtain interesting results in deceptive problems.